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Title |
A MapReduce-based Artificial Neural Network Churn Prediction for Music Streaming Service |
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Author |
Min Chen |
| Citation |
Vol. 22 No. 1 pp. 55-60 |
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Abstract |
Churn prediction is a critical long-term problem for many business like music, games, magazines etc. The churn probability can be used to study many aspects of a business including proactive customer marketing, sales prediction, and churn-sensitive pricing models. It is quite challenging to design machine learning model to predict the customer churn accurately due to the large volume of the time-series data and the temporal issues of the data. In this paper, a parallel artificial neural network is proposed to create a highly-accurate customer churn model on a large customer dataset. The proposed model has achieved significant improvement in the accuracy of churn prediction. The scalability and effectiveness of the proposed algorithm is also studied. |
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Keywords |
Music Streaming, Churn Prediction, MapReduce, Artificial Neural Network |
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